AI Medical Compendium Topic

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Spectrum Analysis, Raman

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Speeding Up the Line-Scan Raman Imaging of Living Cells by Deep Convolutional Neural Network.

Analytical chemistry
Raman imaging is a promising technique that allows the spatial distribution of different components in the sample to be obtained using the molecular fingerprint information on individual species. However, the imaging speed is the bottleneck for the c...

Deep convolutional neural networks for tongue squamous cell carcinoma classification using Raman spectroscopy.

Photodiagnosis and photodynamic therapy
With deep convolutional neural networks and fiber optic Raman spectroscopy, this study presents a novel classification method that discriminates tongue squamous cell carcinoma (TSCC) from non-tumorous tissue. To achieve this purpose, 24 tissues spect...

High-Resolution Raman Microscopic Detection of Follicular Thyroid Cancer Cells with Unsupervised Machine Learning.

The journal of physical chemistry. B
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through compa...

Machine-Learning-Driven Surface-Enhanced Raman Scattering Optophysiology Reveals Multiplexed Metabolite Gradients Near Cells.

ACS nano
The extracellular environment is a complex medium in which cells secrete and consume metabolites. Molecular gradients are thereby created near cells, triggering various biological and physiological responses. However, investigating these molecular gr...

Label-free classification of neurons and glia in neural stem cell cultures using a hyperspectral imaging microscopy combined with machine learning.

Scientific reports
Due to a growing demand for a viable label-free observation method in the biomedical field, many techniques, such as quantitative phase imaging and Raman spectroscopy, have been studied, and a complementary approach, hyperspectral imaging, has also b...

Setting Up a Surface-Enhanced Raman Scattering Database for Artificial-Intelligence-Based Label-Free Discrimination of Tumor Suppressor Genes.

Analytical chemistry
The quality of input data in deep learning is tightly associated with the ultimate performance of the machine learner. Taking advantage of the unique merits of surface-enhanced Raman scattering (SERS) methodology in the collection and construction of...

Analysis of tuberculosis disease through Raman spectroscopy and machine learning.

Photodiagnosis and photodynamic therapy
We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and ...

General Method for the Identification of Crystal Faces Using Raman Spectroscopy Combined with Machine Learning and Application to the Epitaxial Growth of Acetaminophen.

Langmuir : the ACS journal of surfaces and colloids
Crystal morphology is one of the key crystallographic characteristics that governs the macroscopic properties of crystalline materials. The identification of crystal faces, or face indexing, is an important technique that is used to get information r...

Cell type discrimination based on image features of molecular component distribution.

Scientific reports
Machine learning-based cell classifiers use cell images to automate cell-type discrimination, which is increasingly becoming beneficial in biological studies and biomedical applications. Brightfield or fluorescence images are generally employed as th...